Results 181 to 190 of about 849,250 (242)

Skill Biased Technological and Organizational Change: Estimating a Mixed Simultaneous Equation Model Using the IAB Establishment Panel

, 2002
Reinhard Hujer, Marco Caliendo, Dubravko Radić   +2 more
openalex   +1 more source

Estimating 3-D SE(B) Fracture Parameters using 2-D Equations

G. SHEN G., R. Bouchard, W. R. Tyson
openalex   +1 more source

Estimating export equations [PDF]

Applied Economics Letters, 2007
Accurate estimates of the price and income elasticities of exports are valuable for growth policies based on trade promotion. However, not sufficient attention seems to have been paid to the specification of the relative price variable in some influential empirical works.
B Bhaskara Rao, Rup Singh
openaire   +1 more source

Some of the next articles are maybe not open access.

Related searches:

Robust Estimation Through Estimating Equations

Biometrika, 1984
The paper deals with the choice of parameter definition. It develops the concepts of parameter defining function and effective parameter. It also provides theory and techniques for choosing from a given set of robust parameters the one that can most efficiently be estimated. This theory is applied to location parameters.
Godambe, V. P., Thompson, M. E.
openaire   +1 more source

Generalized Estimating Equations

2002
Correlated datasets develop when multiple observations are collected from a sampling unit (e.g., repeated measures of a bank over time, or hormone levels in a breast cancer patient over time), or from clustered data where observations are grouped based on a shared characteristic (e.g., observations on different banks grouped by zip code, or on cancer ...
James W. Hardin, Joseph M. Hilbe
  +6 more sources

Penalized Estimating Equations

Biometrics, 2003
Summary. Penalty models—such as the ridge estimator, the Stein estimator, the bridge estimator, and the Lasso—have been proposed to deal with collinearity in regressions. The Lasso, for instance, has been applied to linear models, logistic regressions, Cox proportional hazard models, and neural networks.
openaire   +3 more sources

Estimating demand equations

European Economic Review, 1977
The sum over individuals of the differentials of demand functions is the basic starting point of the Rotterdam model. In this paper, we show that this global differential can be inverted. Moreover, it can be parametrized according to the lines of the Rotterdam model.
Lise Salvas-Bronsard, D. Leblanc, C. Bronsard   +2 more
openaire   +1 more source

M-Estimation (Estimating Equations)

2012
In Chapter 1 we made the distinction between the parts of a fully specified statistical model. The primary part is the part that is most important for answering the underlying scientific questions. The secondary part consists of all the remaining details of the model.
Denni D Boos, L A Stefanski
openaire   +1 more source

Model Selection in Estimating Equations

Biometrics, 2001
Summary.Model selection is a necessary step in many practical regression analyses. But for methods based on estimating equations, such as the quasi‐likelihood and generalized estimating equation (GEE) approaches, there seem to be few well‐studied model selection techniques.
openaire   +3 more sources

Generalized Estimating Equation

2017
The generalized estimating equation (GEE) uses a quasi-likelihood approach for analyzing data with correlated outcomes. This is an extension of GLM and uses quasi-likelihood method for cluster or repeated outcomes. If observations on outcome variable are repeated, it is likely that the observations are correlated.
M. Ataharul Islam, Rafiqul I. Chowdhury
openaire   +1 more source